110 citations · 157 across the 5 of their papers we have counts for
6 papers
Selecting invalid instruments to improve Mendelian randomization with two-sample summary data
Ashish Patel, Francis J. DiTraglia, Verena Zuber +1
Mendelian randomization (MR) is a widely-used method to estimate the causal relationship between a risk factor and disease. A fundamental part of any MR analysis is to choose appro…
Correlation-Adjusted Regression Survival Scores for High-Dimensional Variable Selection
Thomas Welchowski, Verena Zuber, Matthias Schmid
Background: The development of classification methods for personalized medicine is highly dependent on the identification of predictive genetic markers. In survival analysis it is…
Mendelian randomization with fine-mapped genetic data: choosing from large numbers of correlated instrumental variables
Stephen Burgess, Verena Zuber, Elsa Valdes-Marquez +2
Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of gen…
Task-related edge density (TED) - a new method for revealing large-scale network formation in fMRI data of the human brain
Gabriele Lohmann, Johannes Stelzer, Verena Zuber +4
The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identific…
A novel algorithm for simultaneous SNP selection in high-dimensional genome-wide association studies
Verena Zuber, A. Pedro Duarte Silva, Korbinian Strimmer
Background: Identification of causal SNPs in most genome wide association studies relies on approaches that consider each SNP individually. However, there is a strong correlation s…
Gene ranking and biomarker discovery under correlation
Verena Zuber, Korbinian Strimmer
Biomarker discovery and gene ranking is a standard task in genomic high throughput analysis. Typically, the ordering of markers is based on a stabilized variant of the t-score, suc…